About half of all healthcare worker (HCW) absence can be attributed to gastrointestinal and/or respiratory illness, two sets of conditions that could be caught from patients. HCWs likely experience infection-related illness 1.5 times more than comparable non-HCWs. The financial burden of short-term infection-related absence is difficult to assess because of the possibility that having sick HCWs attend work could be more expensive if infections are then passed on to the patient.
It should be noted that there are both conceptual and methodological challenges in assessing the burden of HCW absences related to infection. First, the bulk of research focuses on physical injury and mental health. There is virtually no US data available on infection-related HCW absences from work, but there are two solid Canadian studies, one of which is particularly informative. There are also numerous other studies from the developing world, with questionable applicability, although they do provide converging estimates of rates.
We are not able to assess the impact on Workers Compensation claims by HCW, but the information available on absenteeism related to infectious symptoms and the high risk of transmission from patients and the environment to HCWs suggests that the impact on Workers Compensation could be significant – and deserving of further analysis. That additional data discovery and analysis is required in partnership/collaboration with experts in Workers Compensation insurance products.
Intended Audience for Data Analysis
- Insurers who provide Workers Compensation coverage
- Hospital systems that are self-insured
- Governments in single-payer countries/regions
- Infection prevention and control consultants/vendors
A global peer-reviewed literature scan was conducted to gather and assess the state-of-the art in measurement and analysis on Healthcare worker infection rates and the financial burden.
A brief analysis was completed from the returned journal articles and an assessment was made regarding conceptual challenges, methodological challenges and general conclusions.
For the purposes of outlining possible paths forward for insurers who provide Workers Compensation coverage, the ‘Suggested Next Step / Action-Items’ has been included.
The first important conceptual challenge is the nature of absenteeism, and how to define it. Belita et al (2013) note that inconsistent definitions between jurisdictions and between research studies complicates the situation. Belita proposes taxonomy with two dimensions: planned vs. unplanned absence, and voluntary vs. involuntary absence. Infection-related illness would be unplanned and involuntary, and is often referred to as “sick absence”. (By contrast, long-term disability is involuntary but planned.)
to what extent are high-status workers reporting to work despite being sick?
The second important conceptual challenge is relating instances of illness to instances of absence. Higher-status healthcare occupations (e.g., physicians, nurse managers) are associated with much lower absentee rates than lower-status occupations (e.g., Gorman et al, 2010). This begs the question of to what extent high-status workers are reporting to work despite being sick, as well as to what extent low-status workers may be malingering.
Both behaviours seriously confound efforts to measure the rate and burden of HCW illness on the healthcare system. However, the problem of sick workers not staying home is particularly vexing because the possibility of infecting patients may mean that lower absentee rates among workers legitimately sick may result in more patients becoming infected.
The major methodological problem in trying to measure the impact of HCW illness/absence is data quality. There are no regulations, nor are there standard approaches to tracking staff illnesses that are not severe. By contrast, workers’ compensation related illness (i.e., long-term disability cases) is very well documented.
Consequently, most research on HCW illness focuses on either mental health or physical injury, or both – but does not track contracting an infection specifically. The situation appears most acute in the US where there is virtually no mention in the research literature of the impact of HCW infection-related sick-absence (i.e., due to respiratory and/or gastrointestinal illness) or the impact on worker compensation claims. There are several studies from the developing world that do provide some convergent findings, noted below. The highest quality research comes from Canada, perhaps spurred by its experience with SARS nearly 15 years ago, which did sicken and kill HCWs at an unprecedented rate.
The highest quality research study is that of Donovan et al (2008), which compared both occupational health records and human resources records in a tertiary care hospital, and compared HCW illness rates to similar non-health occupations. They found that HCWs are 1.5 times as likely as non-HCWs to miss work owing to sickness as well as disability. Documented reports of transmission from patients to HCWs in the literature reported by Donovan et al (2008) include: influenza, tuberculosis, measles, varicella, RSV, and SARS.
Multiple studies indicate that approximately 2/3 of HCWs take short-term “sick leave” each year, that the rate is higher among lower-status occupations, and that half of all of this sick leave is attributed to respiratory and/or gastrointestinal illness (e.g., Donovan et al, 2013; Tripathi et al, 2010).
However, illness itself is only one source of sick-absence among HCWs. Belita et al (2013) report that higher rates of sick absence are associated with larger institutions, urban settings, high workload, unpopular organizational change, being unmarried, and being older. These findings are supported by Borman et al (2010). There is disagreement in the literature about whether sex is a relevant predictor of absence, and it is likely that sex and occupational role are confounded.
It is important to be clear about what type of illness is being considered in research studies (voluntary/involuntary and planned/unplanned) as well as the source of the data itself. Donovan et al (2008) provide an excellent methodological example of how to properly analyze sick-absence data. However, from the existing body of published research, much more can be learned about injury and mental health related to long-term disability than can be learned about sick-absence owing to infections.
We do know that HCWs experience higher rates of work absence for all causes, including respiratory and gastrointestinal illness. The burden on the healthcare system cannot be calculated, however, because of the spectre of lower absenteeism among workers who are ill causing infections among patients.
More research is needed
More research is needed, particularly in the US, to improve our understanding of the relationship between occupational hazards and infection-related illness among HCWs. Further analysis is required on the impact of HCW absenteeism and the financial impact of Worker Compensation claims
Suggested Next Step / Action Items
To increase and improve the data available for analysis of the impact from absenteeism among HCWs on Workers Compensation, particularly in the US, we would suggest the following be considered:
- Confirm the ROI potential internally through better insights into reducing Workers Comp loss claims should better data be available, initially using some of the information provided
- Develop the methodology to calculate the financial loss claim/ financial impact to an insurer offering Workers Comp coverage – and the data necessary to support this methodology
- Incent and engage with preferred partner hospitals for data gathering and discovery
- Provide those hospitals with a tool that will allow them to record the data required to validate the Workers Comp methodology or be coded in such a way that it can be tracked separately
- Develop quality metrics and incentives for wider hospital participation re: data gathering and reporting.
- Integrate these metrics into a full hospital assessment that can be used to assess healthcare institutions for the risk of Workers Comp claims on a going forward basis.
- Belita A, Mbindyo P, English M. (2013). Absenteeism amongst health workers – developing a typology to support empiric work in low-income countries and characterizing reported associations. Human Resources for Health 11(34).
- Donovan TL, Moore KM, VanDenKerkhof EG. (2008). Employee absenteeism based on occupational health visits in an urban tertiary care Canadian hospital. Public Health Nursing 25(6), 565-575.
- Eriksen W, Bruusgaard D, Knardahl S. (2004). Work factors as predictors of sickness absence attributed to airway infections; a three month prospective study of nurses’ aides. Occupational and Environmental Medicine, 61(1), 4551.
- Gorman E, Yu S, Alamgir H. (2010). When healthcare workers get sick: exploring sickness absenteeism in British Columbia, Canada. Work 35, 117-123.
- Tripathi M, Mohan U, Mukesh T, Verma R, Masih L, Hem CP. (2010). Absenteeism among nurses in a tertiary care hospital in India. The National Medical Journal of India 23(3).